Dataset statistics
| Number of variables | 16 |
|---|---|
| Number of observations | 943 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 111.7 KiB |
| Average record size in memory | 121.3 B |
Variable types
| DateTime | 1 |
|---|---|
| Categorical | 8 |
| Numeric | 7 |
username has constant value "levie" | Constant |
tweet has a high cardinality: 943 distinct values | High cardinality |
video is highly correlated with photos | High correlation |
photos is highly correlated with video | High correlation |
replies_count is highly correlated with retweets_count and 1 other fields | High correlation |
retweets_count is highly correlated with replies_count and 1 other fields | High correlation |
likes_count is highly correlated with replies_count and 1 other fields | High correlation |
video is highly correlated with photos | High correlation |
photos is highly correlated with video | High correlation |
replies_count is highly correlated with retweets_count and 1 other fields | High correlation |
retweets_count is highly correlated with replies_count and 1 other fields | High correlation |
likes_count is highly correlated with replies_count and 1 other fields | High correlation |
video is highly correlated with photos | High correlation |
photos is highly correlated with video | High correlation |
replies_count is highly correlated with retweets_count and 1 other fields | High correlation |
retweets_count is highly correlated with replies_count and 1 other fields | High correlation |
likes_count is highly correlated with replies_count and 1 other fields | High correlation |
photos is highly correlated with urls and 1 other fields | High correlation |
bins is highly correlated with percent change | High correlation |
urls is highly correlated with photos | High correlation |
replies_count is highly correlated with likes_count and 1 other fields | High correlation |
video is highly correlated with photos | High correlation |
likes_count is highly correlated with replies_count and 1 other fields | High correlation |
percent change is highly correlated with bins | High correlation |
retweets_count is highly correlated with replies_count and 1 other fields | High correlation |
bins is highly correlated with username | High correlation |
urls is highly correlated with username | High correlation |
cashtags is highly correlated with username | High correlation |
hashtags is highly correlated with username | High correlation |
username is highly correlated with bins and 5 other fields | High correlation |
video is highly correlated with username | High correlation |
mentions is highly correlated with username | High correlation |
tweet is uniformly distributed | Uniform |
date has unique values | Unique |
tweet has unique values | Unique |
photos has 820 (87.0%) zeros | Zeros |
replies_count has 28 (3.0%) zeros | Zeros |
retweets_count has 52 (5.5%) zeros | Zeros |
percent change has 19 (2.0%) zeros | Zeros |
Reproduction
| Analysis started | 2021-09-27 19:02:55.560063 |
|---|---|
| Analysis finished | 2021-09-27 19:03:05.860271 |
| Duration | 10.3 seconds |
| Software version | pandas-profiling v3.0.0 |
| Download configuration | config.json |
| Distinct | 943 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| Minimum | 2016-08-27 09:30:00 |
|---|---|
| Maximum | 2021-07-20 16:00:00 |
| Distinct | 943 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| Everything is funny about Trump's doctor until you realize he's 90% likely to be our future Surgeon General. | 1 |
|---|---|
| @saurabhbhatia Completely agree on both of these! Hope you begin to see these soon-ish... | 1 |
| If I owned this desk I would be asleep 93% of the working day. https://t.co/eAXPPuOTiG | 1 |
| I have yet to run into a business strategy problem that can’t be solved by a pyramid shape or a flywheel. After seeing this TikTok deal play out, I will never again say “ok that’s not realistic” after an episode of Billions. | 1 |
| This is extremely impressive. A well-timed digital strategy that now let’s them own their consumer relationship end-to-end. | 1 |
| Other values (938) |
Length
| Max length | 2175 |
|---|---|
| Median length | 144 |
| Mean length | 208.6680806 |
| Min length | 3 |
Characters and Unicode
| Total characters | 196774 |
|---|---|
| Distinct characters | 175 |
| Distinct categories | 16 ? |
| Distinct scripts | 3 ? |
| Distinct blocks | 12 ? |
Unique
| Unique | 943 ? |
|---|---|
| Unique (%) | 100.0% |
Sample
| 1st row | Everything is funny about Trump's doctor until you realize he's 90% likely to be our future Surgeon General. |
|---|---|
| 2nd row | The Pope's face is one of those, "Shit, it's just a statue of a drone, I thought I was getting a real one" faces. https://t.co/AIURrVdXTt |
| 3rd row | 6,000 people registered for BoxWorks next week! We'll be making major product announcements. And some Trump jokes. https://t.co/EXn9NZAbk0 |
| 4th row | Unlike essentially every other kind of challenge a startup runs into, you probably don't hear "it's not rocket science" much at SpaceX. |
| 5th row | Hopefully it's clear by now that promising taco trucks on every corner would, in fact, be the most electable platform to run on. |
Common Values
| Value | Count | Frequency (%) |
| Everything is funny about Trump's doctor until you realize he's 90% likely to be our future Surgeon General. | 1 | 0.1% |
| @saurabhbhatia Completely agree on both of these! Hope you begin to see these soon-ish... | 1 | 0.1% |
| If I owned this desk I would be asleep 93% of the working day. https://t.co/eAXPPuOTiG | 1 | 0.1% |
| I have yet to run into a business strategy problem that can’t be solved by a pyramid shape or a flywheel. After seeing this TikTok deal play out, I will never again say “ok that’s not realistic” after an episode of Billions. | 1 | 0.1% |
| This is extremely impressive. A well-timed digital strategy that now let’s them own their consumer relationship end-to-end. | 1 | 0.1% |
| You have to hand it to Facebook. They sure do know how to compete when it matters most. https://t.co/F0d58HRIKV | 1 | 0.1% |
| @mcannonbrookes Nah man, fits your portfolio much better... https://t.co/IA4Nl0le9Y Are you really even a tech company if you haven’t explored acquiring TikTok? | 1 | 0.1% |
| Plenty of startup opportunities appear to be in “crowded markets” when in reality the market is just customers solving problems in different ways all looking for a better solution. | 1 | 0.1% |
| We all miss you and are sorry about how the internet played out. | 1 | 0.1% |
| My back of the envelope math says that people are more excited by Kamala Harris than they were Tim Kaine. Boom | 1 | 0.1% |
| Other values (933) | 933 |
Length
| Value | Count | Frequency (%) |
| the | 1216 | 3.7% |
| to | 1035 | 3.2% |
| a | 645 | 2.0% |
| and | 588 | 1.8% |
| of | 552 | 1.7% |
| is | 539 | 1.7% |
| in | 441 | 1.4% |
| this | 423 | 1.3% |
| for | 385 | 1.2% |
| that | 358 | 1.1% |
| Other values (5655) | 26306 |
Most occurring characters
| Value | Count | Frequency (%) |
| 31923 | ||
| e | 17494 | 8.9% |
| t | 14185 | 7.2% |
| o | 12715 | 6.5% |
| a | 11171 | 5.7% |
| n | 10215 | 5.2% |
| i | 10110 | 5.1% |
| s | 9472 | 4.8% |
| r | 9112 | 4.6% |
| l | 6434 | 3.3% |
| Other values (165) | 63943 |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 147762 | |
| Space Separator | 31926 | 16.2% |
| Other Punctuation | 7042 | 3.6% |
| Uppercase Letter | 6730 | 3.4% |
| Decimal Number | 1680 | 0.9% |
| Final Punctuation | 728 | 0.4% |
| Other Symbol | 262 | 0.1% |
| Dash Punctuation | 253 | 0.1% |
| Initial Punctuation | 104 | 0.1% |
| Connector Punctuation | 67 | < 0.1% |
| Other values (6) | 220 | 0.1% |
Most frequent character per category
Other Symbol
| Value | Count | Frequency (%) |
| 😂 | 33 | 12.6% |
| 😀 | 28 | 10.7% |
| 🙏 | 24 | 9.2% |
| 👏 | 17 | 6.5% |
| ☁ | 12 | 4.6% |
| 👍 | 7 | 2.7% |
| 😉 | 5 | 1.9% |
| ❤ | 5 | 1.9% |
| 😄 | 5 | 1.9% |
| ⬇ | 5 | 1.9% |
| Other values (69) | 121 |
Lowercase Letter
| Value | Count | Frequency (%) |
| e | 17494 | |
| t | 14185 | 9.6% |
| o | 12715 | 8.6% |
| a | 11171 | 7.6% |
| n | 10215 | 6.9% |
| i | 10110 | 6.8% |
| s | 9472 | 6.4% |
| r | 9112 | 6.2% |
| l | 6434 | 4.4% |
| h | 6350 | 4.3% |
| Other values (17) | 40504 |
Uppercase Letter
| Value | Count | Frequency (%) |
| T | 744 | 11.1% |
| I | 699 | 10.4% |
| A | 472 | 7.0% |
| S | 460 | 6.8% |
| B | 458 | 6.8% |
| W | 443 | 6.6% |
| C | 313 | 4.7% |
| M | 251 | 3.7% |
| P | 234 | 3.5% |
| N | 231 | 3.4% |
| Other values (16) | 2425 |
Other Punctuation
| Value | Count | Frequency (%) |
| . | 2478 | |
| , | 1136 | |
| / | 942 | 13.4% |
| @ | 865 | 12.3% |
| : | 514 | 7.3% |
| ! | 316 | 4.5% |
| ' | 287 | 4.1% |
| " | 152 | 2.2% |
| * | 115 | 1.6% |
| ? | 103 | 1.5% |
| Other values (4) | 134 | 1.9% |
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 450 | |
| 1 | 277 | |
| 2 | 241 | |
| 5 | 128 | 7.6% |
| 9 | 108 | 6.4% |
| 3 | 105 | 6.2% |
| 6 | 98 | 5.8% |
| 4 | 95 | 5.7% |
| 8 | 95 | 5.7% |
| 7 | 83 | 4.9% |
Math Symbol
| Value | Count | Frequency (%) |
| + | 17 | |
| ~ | 8 | |
| = | 5 | 15.6% |
| ≠ | 1 | 3.1% |
| ⤵ | 1 | 3.1% |
Space Separator
| Value | Count | Frequency (%) |
| 31923 | ||
| 3 | < 0.1% |
Dash Punctuation
| Value | Count | Frequency (%) |
| - | 227 | |
| — | 26 | 10.3% |
Final Punctuation
| Value | Count | Frequency (%) |
| ’ | 628 | |
| ” | 100 | 13.7% |
Initial Punctuation
| Value | Count | Frequency (%) |
| “ | 102 | |
| ‘ | 2 | 1.9% |
Open Punctuation
| Value | Count | Frequency (%) |
| ( | 41 |
Close Punctuation
| Value | Count | Frequency (%) |
| ) | 49 |
Currency Symbol
| Value | Count | Frequency (%) |
| $ | 66 |
Connector Punctuation
| Value | Count | Frequency (%) |
| _ | 67 |
Nonspacing Mark
| Value | Count | Frequency (%) |
| ️ | 27 |
Format
| Value | Count | Frequency (%) |
| | 5 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 154492 | |
| Common | 42250 | 21.5% |
| Inherited | 32 | < 0.1% |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 31923 | ||
| . | 2478 | 5.9% |
| , | 1136 | 2.7% |
| / | 942 | 2.2% |
| @ | 865 | 2.0% |
| ’ | 628 | 1.5% |
| : | 514 | 1.2% |
| 0 | 450 | 1.1% |
| ! | 316 | 0.7% |
| ' | 287 | 0.7% |
| Other values (110) | 2711 | 6.4% |
Latin
| Value | Count | Frequency (%) |
| e | 17494 | 11.3% |
| t | 14185 | 9.2% |
| o | 12715 | 8.2% |
| a | 11171 | 7.2% |
| n | 10215 | 6.6% |
| i | 10110 | 6.5% |
| s | 9472 | 6.1% |
| r | 9112 | 5.9% |
| l | 6434 | 4.2% |
| h | 6350 | 4.1% |
| Other values (43) | 47234 |
Inherited
| Value | Count | Frequency (%) |
| ️ | 27 | |
| | 5 | 15.6% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 195615 | |
| Punctuation | 863 | 0.4% |
| Emoticons | 141 | 0.1% |
| None | 87 | < 0.1% |
| VS | 27 | < 0.1% |
| Misc Symbols | 17 | < 0.1% |
| Dingbats | 9 | < 0.1% |
| Enclosed Alphanum Sup | 6 | < 0.1% |
| Latin 1 Sup | 5 | < 0.1% |
| Letterlike Symbols | 2 | < 0.1% |
| Other values (2) | 2 | < 0.1% |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 31923 | ||
| e | 17494 | 8.9% |
| t | 14185 | 7.3% |
| o | 12715 | 6.5% |
| a | 11171 | 5.7% |
| n | 10215 | 5.2% |
| i | 10110 | 5.2% |
| s | 9472 | 4.8% |
| r | 9112 | 4.7% |
| l | 6434 | 3.3% |
| Other values (75) | 62784 |
Emoticons
| Value | Count | Frequency (%) |
| 😂 | 33 | |
| 😀 | 28 | |
| 🙏 | 24 | |
| 😉 | 5 | 3.5% |
| 😄 | 5 | 3.5% |
| 😳 | 4 | 2.8% |
| 😬 | 4 | 2.8% |
| 😎 | 4 | 2.8% |
| 😢 | 3 | 2.1% |
| 😟 | 3 | 2.1% |
| Other values (20) | 28 |
Latin 1 Sup
| Value | Count | Frequency (%) |
| 3 | ||
| é | 2 |
Enclosed Alphanum Sup
| Value | Count | Frequency (%) |
| 🇺 | 3 | |
| 🇸 | 2 | |
| 🇪 | 1 | 16.7% |
None
| Value | Count | Frequency (%) |
| 👏 | 17 | |
| 👍 | 7 | 8.0% |
| ⬇ | 5 | 5.7% |
| 🚀 | 5 | 5.7% |
| 🔥 | 4 | 4.6% |
| 🤪 | 3 | 3.4% |
| 🎉 | 3 | 3.4% |
| 👇 | 3 | 3.4% |
| 🤯 | 3 | 3.4% |
| 🧐 | 3 | 3.4% |
| Other values (28) | 34 |
Math Operators
| Value | Count | Frequency (%) |
| ≠ | 1 |
Misc Symbols
| Value | Count | Frequency (%) |
| ☁ | 12 | |
| ♂ | 2 | 11.8% |
| ♀ | 2 | 11.8% |
| ⚔ | 1 | 5.9% |
VS
| Value | Count | Frequency (%) |
| ️ | 27 |
Dingbats
| Value | Count | Frequency (%) |
| ❤ | 5 | |
| ✅ | 3 | |
| ✊ | 1 | 11.1% |
Punctuation
| Value | Count | Frequency (%) |
| ’ | 628 | |
| “ | 102 | 11.8% |
| ” | 100 | 11.6% |
| — | 26 | 3.0% |
| | 5 | 0.6% |
| ‘ | 2 | 0.2% |
Letterlike Symbols
| Value | Count | Frequency (%) |
| ™ | 2 |
Sup Arrows B
| Value | Count | Frequency (%) |
| ⤵ | 1 |
| Distinct | 1 |
|---|---|
| Distinct (%) | 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| levie |
|---|
Length
| Max length | 5 |
|---|---|
| Median length | 5 |
| Mean length | 5 |
| Min length | 5 |
Characters and Unicode
| Total characters | 4715 |
|---|---|
| Distinct characters | 4 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | levie |
|---|---|
| 2nd row | levie |
| 3rd row | levie |
| 4th row | levie |
| 5th row | levie |
Common Values
| Value | Count | Frequency (%) |
| levie | 943 |
Length
Pie chart
| Value | Count | Frequency (%) |
| levie | 943 |
Most occurring characters
| Value | Count | Frequency (%) |
| e | 1886 | |
| l | 943 | |
| v | 943 | |
| i | 943 |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 4715 |
Most frequent character per category
Lowercase Letter
| Value | Count | Frequency (%) |
| e | 1886 | |
| l | 943 | |
| v | 943 | |
| i | 943 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 4715 |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| e | 1886 | |
| l | 943 | |
| v | 943 | |
| i | 943 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 4715 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| e | 1886 | |
| l | 943 | |
| v | 943 | |
| i | 943 |
| Distinct | 5 |
|---|---|
| Distinct (%) | 0.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| 0 | |
|---|---|
| 1 | 58 |
| 2 | 17 |
| 4 | 1 |
| 3 | 1 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 943 |
|---|---|
| Distinct characters | 5 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 2 ? |
|---|---|
| Unique (%) | 0.2% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 866 | |
| 1 | 58 | 6.2% |
| 2 | 17 | 1.8% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Length
Pie chart
| Value | Count | Frequency (%) |
| 0 | 866 | |
| 1 | 58 | 6.2% |
| 2 | 17 | 1.8% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 866 | |
| 1 | 58 | 6.2% |
| 2 | 17 | 1.8% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 943 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 866 | |
| 1 | 58 | 6.2% |
| 2 | 17 | 1.8% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 943 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 866 | |
| 1 | 58 | 6.2% |
| 2 | 17 | 1.8% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 943 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 866 | |
| 1 | 58 | 6.2% |
| 2 | 17 | 1.8% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| 0 | |
|---|---|
| 1 | 11 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 943 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 932 | |
| 1 | 11 | 1.2% |
Length
Pie chart
| Value | Count | Frequency (%) |
| 0 | 932 | |
| 1 | 11 | 1.2% |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 932 | |
| 1 | 11 | 1.2% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 943 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 932 | |
| 1 | 11 | 1.2% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 943 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 932 | |
| 1 | 11 | 1.2% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 943 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 932 | |
| 1 | 11 | 1.2% |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| 0 | |
|---|---|
| 1 | 2 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 943 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 941 | |
| 1 | 2 | 0.2% |
Length
Pie chart
| Value | Count | Frequency (%) |
| 0 | 941 | |
| 1 | 2 | 0.2% |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 941 | |
| 1 | 2 | 0.2% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 943 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 941 | |
| 1 | 2 | 0.2% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 943 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 941 | |
| 1 | 2 | 0.2% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 943 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 941 | |
| 1 | 2 | 0.2% |
| Distinct | 5 |
|---|---|
| Distinct (%) | 0.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| 0 | |
|---|---|
| 1 | |
| 2 | 5 |
| 4 | 1 |
| 3 | 1 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 943 |
|---|---|
| Distinct characters | 5 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 2 ? |
|---|---|
| Unique (%) | 0.2% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 1 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 808 | |
| 1 | 128 | 13.6% |
| 2 | 5 | 0.5% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Length
Pie chart
| Value | Count | Frequency (%) |
| 0 | 808 | |
| 1 | 128 | 13.6% |
| 2 | 5 | 0.5% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 808 | |
| 1 | 128 | 13.6% |
| 2 | 5 | 0.5% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 943 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 808 | |
| 1 | 128 | 13.6% |
| 2 | 5 | 0.5% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 943 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 808 | |
| 1 | 128 | 13.6% |
| 2 | 5 | 0.5% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 943 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 808 | |
| 1 | 128 | 13.6% |
| 2 | 5 | 0.5% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
| Distinct | 6 |
|---|---|
| Distinct (%) | 0.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.1527041357 |
| Minimum | 0 |
|---|---|
| Maximum | 7 |
| Zeros | 820 |
| Zeros (%) | 87.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 1 |
| Maximum | 7 |
| Range | 7 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 0.4630859798 |
|---|---|
| Coefficient of variation (CV) | 3.032569993 |
| Kurtosis | 58.70723629 |
| Mean | 0.1527041357 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 5.657196384 |
| Sum | 144 |
| Variance | 0.2144486247 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 0 | 820 | |
| 1 | 110 | 11.7% |
| 2 | 10 | 1.1% |
| 7 | 1 | 0.1% |
| 3 | 1 | 0.1% |
| 4 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 0 | 820 | |
| 1 | 110 | 11.7% |
| 2 | 10 | 1.1% |
| 3 | 1 | 0.1% |
| 4 | 1 | 0.1% |
| 7 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 7 | 1 | 0.1% |
| 4 | 1 | 0.1% |
| 3 | 1 | 0.1% |
| 2 | 10 | 1.1% |
| 1 | 110 | 11.7% |
| 0 | 820 |
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.5 KiB |
| 0 | |
|---|---|
| 1 | |
| 2 | 6 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 943 |
|---|---|
| Distinct characters | 3 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 1 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 785 | |
| 1 | 152 | 16.1% |
| 2 | 6 | 0.6% |
Length
Pie chart
| Value | Count | Frequency (%) |
| 0 | 785 | |
| 1 | 152 | 16.1% |
| 2 | 6 | 0.6% |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 785 | |
| 1 | 152 | 16.1% |
| 2 | 6 | 0.6% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 943 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 785 | |
| 1 | 152 | 16.1% |
| 2 | 6 | 0.6% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 943 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 785 | |
| 1 | 152 | 16.1% |
| 2 | 6 | 0.6% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 943 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 785 | |
| 1 | 152 | 16.1% |
| 2 | 6 | 0.6% |
replies_count
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONZEROS| Distinct | 165 |
|---|---|
| Distinct (%) | 17.5% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 42.69141039 |
| Minimum | 0 |
|---|---|
| Maximum | 1373 |
| Zeros | 28 |
| Zeros (%) | 3.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 11 |
| median | 23 |
| Q3 | 47.5 |
| 95-th percentile | 143 |
| Maximum | 1373 |
| Range | 1373 |
| Interquartile range (IQR) | 36.5 |
Descriptive statistics
| Standard deviation | 71.43682494 |
|---|---|
| Coefficient of variation (CV) | 1.673330168 |
| Kurtosis | 137.4067264 |
| Mean | 42.69141039 |
| Median Absolute Deviation (MAD) | 16 |
| Skewness | 8.903154451 |
| Sum | 40258 |
| Variance | 5103.219958 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 1 | 31 | 3.3% |
| 13 | 31 | 3.3% |
| 0 | 28 | 3.0% |
| 5 | 24 | 2.5% |
| 12 | 23 | 2.4% |
| 3 | 23 | 2.4% |
| 6 | 22 | 2.3% |
| 14 | 22 | 2.3% |
| 9 | 22 | 2.3% |
| 8 | 20 | 2.1% |
| Other values (155) | 697 |
| Value | Count | Frequency (%) |
| 0 | 28 | |
| 1 | 31 | |
| 2 | 18 | |
| 3 | 23 | |
| 4 | 17 | |
| 5 | 24 | |
| 6 | 22 | |
| 7 | 14 | |
| 8 | 20 | |
| 9 | 22 |
| Value | Count | Frequency (%) |
| 1373 | 1 | |
| 658 | 1 | |
| 514 | 1 | |
| 449 | 1 | |
| 402 | 1 | |
| 379 | 1 | |
| 315 | 1 | |
| 298 | 1 | |
| 296 | 1 | |
| 257 | 1 |
retweets_count
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONZEROS| Distinct | 398 |
|---|---|
| Distinct (%) | 42.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 216.4220573 |
| Minimum | 0 |
|---|---|
| Maximum | 8667 |
| Zeros | 52 |
| Zeros (%) | 5.5% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 32 |
| median | 95 |
| Q3 | 227 |
| 95-th percentile | 803.9 |
| Maximum | 8667 |
| Range | 8667 |
| Interquartile range (IQR) | 195 |
Descriptive statistics
| Standard deviation | 442.1322995 |
|---|---|
| Coefficient of variation (CV) | 2.042916998 |
| Kurtosis | 149.1851339 |
| Mean | 216.4220573 |
| Median Absolute Deviation (MAD) | 79 |
| Skewness | 9.369359817 |
| Sum | 204086 |
| Variance | 195480.9703 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 0 | 52 | 5.5% |
| 1 | 21 | 2.2% |
| 27 | 11 | 1.2% |
| 46 | 10 | 1.1% |
| 2 | 10 | 1.1% |
| 14 | 9 | 1.0% |
| 13 | 9 | 1.0% |
| 12 | 9 | 1.0% |
| 23 | 8 | 0.8% |
| 17 | 8 | 0.8% |
| Other values (388) | 796 |
| Value | Count | Frequency (%) |
| 0 | 52 | |
| 1 | 21 | |
| 2 | 10 | 1.1% |
| 3 | 7 | 0.7% |
| 4 | 6 | 0.6% |
| 5 | 3 | 0.3% |
| 6 | 6 | 0.6% |
| 7 | 2 | 0.2% |
| 8 | 6 | 0.6% |
| 9 | 6 | 0.6% |
| Value | Count | Frequency (%) |
| 8667 | 1 | |
| 3392 | 1 | |
| 3205 | 1 | |
| 2479 | 1 | |
| 2401 | 1 | |
| 2110 | 1 | |
| 2016 | 1 | |
| 2013 | 1 | |
| 1951 | 1 | |
| 1931 | 1 |
| Distinct | 780 |
|---|---|
| Distinct (%) | 82.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1565.697773 |
| Minimum | 0 |
|---|---|
| Maximum | 47412 |
| Zeros | 1 |
| Zeros (%) | 0.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 26.1 |
| Q1 | 370.5 |
| median | 826 |
| Q3 | 1786 |
| 95-th percentile | 5187.5 |
| Maximum | 47412 |
| Range | 47412 |
| Interquartile range (IQR) | 1415.5 |
Descriptive statistics
| Standard deviation | 2667.338067 |
|---|---|
| Coefficient of variation (CV) | 1.703609798 |
| Kurtosis | 109.318219 |
| Mean | 1565.697773 |
| Median Absolute Deviation (MAD) | 559 |
| Skewness | 8.091379877 |
| Sum | 1476453 |
| Variance | 7114692.362 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 5 | 6 | 0.6% |
| 55 | 4 | 0.4% |
| 4 | 4 | 0.4% |
| 1092 | 4 | 0.4% |
| 752 | 4 | 0.4% |
| 15 | 4 | 0.4% |
| 7 | 4 | 0.4% |
| 133 | 4 | 0.4% |
| 8 | 3 | 0.3% |
| 557 | 3 | 0.3% |
| Other values (770) | 903 |
| Value | Count | Frequency (%) |
| 0 | 1 | 0.1% |
| 1 | 1 | 0.1% |
| 2 | 2 | 0.2% |
| 3 | 1 | 0.1% |
| 4 | 4 | |
| 5 | 6 | |
| 6 | 1 | 0.1% |
| 7 | 4 | |
| 8 | 3 | |
| 9 | 3 |
| Value | Count | Frequency (%) |
| 47412 | 1 | |
| 28419 | 1 | |
| 21918 | 1 | |
| 17469 | 1 | |
| 15575 | 1 | |
| 13656 | 1 | |
| 11068 | 1 | |
| 10889 | 1 | |
| 10593 | 1 | |
| 10479 | 1 |
number of tweets
Real number (ℝ≥0)
| Distinct | 15 |
|---|---|
| Distinct (%) | 1.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1.80699894 |
| Minimum | 1 |
|---|---|
| Maximum | 15 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 1 |
| Q1 | 1 |
| median | 1 |
| Q3 | 2 |
| 95-th percentile | 5 |
| Maximum | 15 |
| Range | 14 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 1.601775092 |
|---|---|
| Coefficient of variation (CV) | 0.8864283522 |
| Kurtosis | 18.18554396 |
| Mean | 1.80699894 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 3.628235866 |
| Sum | 1704 |
| Variance | 2.565683447 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 1 | 594 | |
| 2 | 183 | 19.4% |
| 3 | 74 | 7.8% |
| 4 | 40 | 4.2% |
| 5 | 21 | 2.2% |
| 6 | 10 | 1.1% |
| 7 | 7 | 0.7% |
| 8 | 4 | 0.4% |
| 10 | 3 | 0.3% |
| 12 | 2 | 0.2% |
| Other values (5) | 5 | 0.5% |
| Value | Count | Frequency (%) |
| 1 | 594 | |
| 2 | 183 | 19.4% |
| 3 | 74 | 7.8% |
| 4 | 40 | 4.2% |
| 5 | 21 | 2.2% |
| 6 | 10 | 1.1% |
| 7 | 7 | 0.7% |
| 8 | 4 | 0.4% |
| 9 | 1 | 0.1% |
| 10 | 3 | 0.3% |
| Value | Count | Frequency (%) |
| 15 | 1 | 0.1% |
| 14 | 1 | 0.1% |
| 13 | 1 | 0.1% |
| 12 | 2 | 0.2% |
| 11 | 1 | 0.1% |
| 10 | 3 | 0.3% |
| 9 | 1 | 0.1% |
| 8 | 4 | 0.4% |
| 7 | 7 | |
| 6 | 10 |
price
Real number (ℝ≥0)
| Distinct | 732 |
|---|---|
| Distinct (%) | 77.6% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 18.67166823 |
| Minimum | 9.06000042 |
|---|---|
| Maximum | 29.25 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | 9.06000042 |
|---|---|
| 5-th percentile | 14.17400004 |
| Q1 | 16.91333357 |
| median | 18.13499928 |
| Q3 | 20.32208308 |
| 95-th percentile | 24.79199924 |
| Maximum | 29.25 |
| Range | 20.18999958 |
| Interquartile range (IQR) | 3.408749501 |
Descriptive statistics
| Standard deviation | 3.122952749 |
|---|---|
| Coefficient of variation (CV) | 0.1672562253 |
| Kurtosis | 0.575870231 |
| Mean | 18.67166823 |
| Median Absolute Deviation (MAD) | 1.534998894 |
| Skewness | 0.4414069218 |
| Sum | 17607.38314 |
| Variance | 9.752833875 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 20.88999939 | 6 | 0.6% |
| 18.79999924 | 6 | 0.6% |
| 18.36000061 | 5 | 0.5% |
| 18.55999947 | 5 | 0.5% |
| 18.04999924 | 5 | 0.5% |
| 16.92000008 | 4 | 0.4% |
| 17.14999962 | 4 | 0.4% |
| 17.37999916 | 4 | 0.4% |
| 17.54999924 | 4 | 0.4% |
| 17.79999924 | 4 | 0.4% |
| Other values (722) | 896 |
| Value | Count | Frequency (%) |
| 9.06000042 | 1 | |
| 9.119999886 | 1 | |
| 9.210000038 | 1 | |
| 9.229999542 | 1 | |
| 9.590000153 | 1 | |
| 9.756666819 | 1 | |
| 10.45333322 | 1 | |
| 10.60000038 | 1 | |
| 10.93000031 | 1 | |
| 11.5 | 1 |
| Value | Count | Frequency (%) |
| 29.25 | 1 | |
| 28.42000008 | 1 | |
| 28 | 1 | |
| 27.35000038 | 1 | |
| 27.31999969 | 1 | |
| 27.21250057 | 1 | |
| 27.20999972 | 1 | |
| 27.20000076 | 1 | |
| 26.82500029 | 1 | |
| 26.7750001 | 1 |
| Distinct | 921 |
|---|---|
| Distinct (%) | 97.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.001000680484 |
| Minimum | -0.1438071139 |
|---|---|
| Maximum | 0.2148070316 |
| Zeros | 19 |
| Zeros (%) | 2.0% |
| Negative | 438 |
| Negative (%) | 46.4% |
| Memory size | 7.5 KiB |
Quantile statistics
| Minimum | -0.1438071139 |
|---|---|
| 5-th percentile | -0.0295389959 |
| Q1 | -0.00768489594 |
| median | 0.000870460276 |
| Q3 | 0.009556436548 |
| 95-th percentile | 0.03048687252 |
| Maximum | 0.2148070316 |
| Range | 0.3586141455 |
| Interquartile range (IQR) | 0.01724133249 |
Descriptive statistics
| Standard deviation | 0.02125458754 |
|---|---|
| Coefficient of variation (CV) | 21.24013396 |
| Kurtosis | 16.50105948 |
| Mean | 0.001000680484 |
| Median Absolute Deviation (MAD) | 0.008582620687 |
| Skewness | 1.12081547 |
| Sum | 0.9436416968 |
| Variance | 0.0004517574914 |
| Monotonicity | Not monotonic |
| Value | Count | Frequency (%) |
| 0 | 19 | 2.0% |
| 0.007084989273 | 2 | 0.2% |
| 0.02461536114 | 2 | 0.2% |
| 0.001618930285 | 2 | 0.2% |
| -0.005875462913 | 2 | 0.2% |
| -0.0005817468628 | 1 | 0.1% |
| -0.001663896327 | 1 | 0.1% |
| 0.003888871935 | 1 | 0.1% |
| -0.001660142767 | 1 | 0.1% |
| 0.003335156571 | 1 | 0.1% |
| Other values (911) | 911 |
| Value | Count | Frequency (%) |
| -0.1438071139 | 1 | |
| -0.08737868173 | 1 | |
| -0.07826083639 | 1 | |
| -0.07729682187 | 1 | |
| -0.07436016785 | 1 | |
| -0.06822073405 | 1 | |
| -0.0661435143 | 1 | |
| -0.06083515091 | 1 | |
| -0.0599103952 | 1 | |
| -0.05968925344 | 1 |
| Value | Count | Frequency (%) |
| 0.2148070316 | 1 | |
| 0.1130333949 | 1 | |
| 0.1119176284 | 1 | |
| 0.1091000575 | 1 | |
| 0.09020216115 | 1 | |
| 0.08215483381 | 1 | |
| 0.07986306695 | 1 | |
| 0.07846779712 | 1 | |
| 0.06603331817 | 1 | |
| 0.06311823747 | 1 |
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 1.2 KiB |
| no change | |
|---|---|
| rise | |
| drop |
Length
| Max length | 9 |
|---|---|
| Median length | 9 |
| Mean length | 8.050901379 |
| Min length | 4 |
Characters and Unicode
| Total characters | 7592 |
|---|---|
| Distinct characters | 13 |
| Distinct categories | 2 ? |
| Distinct scripts | 2 ? |
| Distinct blocks | 1 ? |
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | no change |
|---|---|
| 2nd row | no change |
| 3rd row | no change |
| 4th row | rise |
| 5th row | no change |
Common Values
| Value | Count | Frequency (%) |
| no change | 764 | |
| rise | 93 | 9.9% |
| drop | 86 | 9.1% |
Length
Pie chart
| Value | Count | Frequency (%) |
| no | 764 | |
| change | 764 | |
| rise | 93 | 5.4% |
| drop | 86 | 5.0% |
Most occurring characters
| Value | Count | Frequency (%) |
| n | 1528 | |
| e | 857 | |
| o | 850 | |
| 764 | ||
| c | 764 | |
| h | 764 | |
| a | 764 | |
| g | 764 | |
| r | 179 | 2.4% |
| i | 93 | 1.2% |
| Other values (3) | 265 | 3.5% |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 6828 | |
| Space Separator | 764 | 10.1% |
Most frequent character per category
Lowercase Letter
| Value | Count | Frequency (%) |
| n | 1528 | |
| e | 857 | |
| o | 850 | |
| c | 764 | |
| h | 764 | |
| a | 764 | |
| g | 764 | |
| r | 179 | 2.6% |
| i | 93 | 1.4% |
| s | 93 | 1.4% |
| Other values (2) | 172 | 2.5% |
Space Separator
| Value | Count | Frequency (%) |
| 764 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 6828 | |
| Common | 764 | 10.1% |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| n | 1528 | |
| e | 857 | |
| o | 850 | |
| c | 764 | |
| h | 764 | |
| a | 764 | |
| g | 764 | |
| r | 179 | 2.6% |
| i | 93 | 1.4% |
| s | 93 | 1.4% |
| Other values (2) | 172 | 2.5% |
Common
| Value | Count | Frequency (%) |
| 764 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 7592 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| n | 1528 | |
| e | 857 | |
| o | 850 | |
| 764 | ||
| c | 764 | |
| h | 764 | |
| a | 764 | |
| g | 764 | |
| r | 179 | 2.4% |
| i | 93 | 1.2% |
| Other values (3) | 265 | 3.5% |
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.First rows
| date | tweet | username | mentions | hashtags | cashtags | video | photos | urls | replies_count | retweets_count | likes_count | number of tweets | price | percent change | bins | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2016-08-27 09:30:00 | Everything is funny about Trump's doctor until you realize he's 90% likely to be our future Surgeon General. | levie | 0 | 0 | 0 | 0 | 0 | 0 | 31 | 147 | 577 | 1 | 13.130 | 0.006130 | no change |
| 1 | 2016-08-29 16:00:00 | The Pope's face is one of those, "Shit, it's just a statue of a drone, I thought I was getting a real one" faces. https://t.co/AIURrVdXTt | levie | 0 | 0 | 0 | 1 | 1 | 0 | 8 | 111 | 338 | 1 | 13.290 | 0.018391 | no change |
| 2 | 2016-08-30 16:00:00 | 6,000 people registered for BoxWorks next week! We'll be making major product announcements. And some Trump jokes. https://t.co/EXn9NZAbk0 | levie | 0 | 0 | 0 | 0 | 0 | 1 | 5 | 34 | 192 | 1 | 13.320 | 0.000000 | no change |
| 3 | 2016-09-01 16:00:00 | Unlike essentially every other kind of challenge a startup runs into, you probably don't hear "it's not rocket science" much at SpaceX. | levie | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 355 | 928 | 1 | 13.980 | 0.055094 | rise |
| 4 | 2016-09-02 16:00:00 | Hopefully it's clear by now that promising taco trucks on every corner would, in fact, be the most electable platform to run on. | levie | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 186 | 650 | 1 | 14.140 | 0.010000 | no change |
| 5 | 2016-09-03 09:30:00 | BoxWorks is now 5 days away! Grab a free expo pass to join us for the keynotes here: https://t.co/4Pgi6yBzXa https://t.co/4CtLndUeUz | levie | 0 | 0 | 0 | 1 | 1 | 1 | 18 | 64 | 329 | 1 | 14.035 | -0.007426 | no change |
| 6 | 2016-09-04 09:30:00 | Building an enterprise software company is 95% technology and 5% channeling your inner Taylor Swift. https://t.co/vrXrXt55Rr | levie | 0 | 0 | 0 | 1 | 1 | 0 | 20 | 138 | 503 | 1 | 14.070 | -0.006531 | no change |
| 7 | 2016-09-05 09:30:00 | "Oh sure, this seems like a totally safe and normal Airbnb to stay in." https://t.co/vfulGB7ftx | levie | 0 | 0 | 0 | 1 | 1 | 0 | 13 | 83 | 479 | 1 | 14.105 | -0.005640 | no change |
| 8 | 2016-09-06 09:30:00 | 7,000 people registered for BoxWorks this week! If you can't make it (why!? 😢😟😞😗) we'll be streaming live here: https://t.co/EXn9NZAbk0 | levie | 0 | 0 | 0 | 0 | 0 | 1 | 6 | 38 | 158 | 1 | 14.140 | -0.004751 | no change |
| 9 | 2016-09-07 16:00:00 | Steps for a great morning: 1. Load https://t.co/OefY681YEc 2. Load https://t.co/MFBvDV5Hnj 3. Experience all your tech wishes come true | levie | 0 | 0 | 0 | 0 | 0 | 2 | 7 | 28 | 155 | 1 | 14.520 | 0.013967 | no change |
Last rows
| date | tweet | username | mentions | hashtags | cashtags | video | photos | urls | replies_count | retweets_count | likes_count | number of tweets | price | percent change | bins | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 933 | 2021-07-06 16:00:00 | @zlurie Adding $55B in market cap. Heck of a first day on the job! | levie | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 34 | 1 | 26.340000 | -0.018994 | no change |
| 934 | 2021-07-07 09:30:00 | Could not be more proud or excited for how the Box team is cranking on our product roadmap right now. Lots and lots of epic innovation coming soon for customers this summer and fall! | levie | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 6 | 236 | 1 | 26.500000 | 0.006074 | no change |
| 935 | 2021-07-07 16:00:00 | Excited to partner with BT as they continue to leverage the Box Content Cloud! https://t.co/lJQ2PIQSas | levie | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 55 | 1 | 25.610001 | -0.033585 | drop |
| 936 | 2021-07-09 09:30:00 | @apoorva_mehta @fidjissimo Congratttttttts! | levie | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 25.110001 | -0.000398 | no change |
| 937 | 2021-07-11 16:00:00 | Crazy https://t.co/dRQ7MSW2B4 | levie | 0 | 0 | 0 | 1 | 1 | 0 | 23 | 105 | 1479 | 1 | 24.843333 | -0.015586 | no change |
| 938 | 2021-07-14 16:00:00 | If you’re not killing products you’re not working on enough risky ideas. Interesting to see which states are all for free markets, until they’re not. | levie | 0 | 0 | 0 | 0 | 0 | 0 | 39 | 188 | 1936 | 2 | 23.840000 | -0.018930 | no change |
| 939 | 2021-07-17 16:00:00 | @DavidSacks Will text him now @DavidSacks Left here, reporting for duty. For sure came from a lab. @micsolana @rabois Never said mass censorship 😉. Said mass distribution has consequences. I think plenty of innovation starts out great and then we see the follow on effects of it, so it’s worth being critical and introspective of this. Also, FWIW I have no solution to offer, just complaints 😀 @alanknit @rabois Well I guess Keith wins this round, yet again! @peteryared @rabois @raohackr Unless you’ve been going to Lauren Boebert rallies, you might not be the demographic where our issue lies. But also on category #2 that just is a bad public health strategy. @rabois @raohackr Notice I didn’t say Scientists™. I said science 😀. Just talking about vaccines here. @raohackr @rabois Yeah, not going to work in a heavily politicized public health crisis where large groups willfully ignore science. Speech vs. speech isn’t going to solve anything. Anyway, it is what it is 😀. @raohackr @rabois There are 0 things Biden admin could do to convince a meaningful portion of US to get vaccinated when it has become fully politicized and weaponized as an issue. They are a centralized entity fighting a decentralized war 10X their size with the same informational tools. @rabois I don’t think the government should control what’s on social media. Largely, I think social media platforms should decide. But I also think we don’t fully understand how we’re supposed to resolve the consequence of mass distribution of dangerous content. @rabois Alternatively: if people are mad about everyone having a bazooka, just wait until they realize what pistols are used for. And bow and arrows. And cutlery. @rabois Come on though 😀. 17 years into social media we can thoughtfully differentiate small group communication from mass distribution. If we can’t critically think about the consequences of that, we really don’t understand what tech unleashes on the world. | levie | 0 | 0 | 0 | 0 | 0 | 0 | 48 | 13 | 638 | 11 | 23.303333 | -0.009773 | no change |
| 940 | 2021-07-19 09:30:00 | @rowantrollope @ericsyuan 🥳🎉🥂 congrats you two! | levie | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 16 | 1 | 23.260000 | 0.005331 | no change |
| 941 | 2021-07-20 09:30:00 | Amazing https://t.co/YGDtOVvm92 | levie | 0 | 0 | 0 | 1 | 1 | 0 | 3 | 6 | 145 | 1 | 23.129999 | 0.006966 | no change |
| 942 | 2021-07-20 16:00:00 | This is a very sad take on entrepreneurship Space innovation from many ventures is just plain win-win-win. More funding of research that will lead to unexpected discoveries, more rocket scientists, more knowledge about the universe, and of course the possibility of tourism and expanding to other planets. | levie | 0 | 0 | 0 | 0 | 0 | 0 | 63 | 80 | 970 | 2 | 23.740000 | 0.026373 | rise |